1. Technical Field
This invention generally relates to massively parallel computing systems and development, and more specifically relates to an application checkpointing method and apparatus.
2. Background Art
Supercomputers continue to be developed to tackle sophisticated computing jobs. These computers are particularly useful to scientists for high performance computing (HPC) applications including life sciences, financial modeling, hydrodynamics, quantum chemistry, molecular dynamics, astronomy and space research and climate modeling. Supercomputer developers have focused on massively parallel computer structures to solve this need for increasingly complex computing needs. One such massively parallel computer being developed by International Business Machines Corporation (IBM) is the Blue Gene system. The Blue Gene system is a scalable system in which the maximum number of compute nodes is 65,536. Each node consists of a single ASIC (application specific integrated circuit and memory. Each node typically has 512 megabytes of local memory. The full computer would be housed in 64 racks or cabinets with 32 node boards in each. Each node board has 32 processors and the associated memory for each processor.
The Blue Gene supercomputer's 65,536 computational nodes and 1024 I/O processors are arranged into both a logical tree network and a logical 3-dimensional torus network. Blue Gene can be described as a compute node core with an I/O node surface. Each I/O node handles the input and output function of 64 compute nodes. The 110 nodes have no local storage. The I/O nodes are connected to the compute nodes through the tree network and also have functional wide area network capabilities through its built in gigabit ethernet network.
On a super computer system like Blue Gene, the mean time before failure of any hardware or software component may be measured in hours and the complex computing programs describe above may take several hours to several days to run. If a machine is brought down for maintenance, software upgrades, or because an application crashes there needs to be a way to store the current state of the computer so that execution can resume where it left off when the hardware is able to continue executing. The process of saving the state of a running application is known in the art as “checkpointing.” Thus, checkpointing the application saves the state of the application in a recoverable fashion so that the application can continue from the checkpoint location. The traditional way to do checkpointing is to take a memory “snapshot” of the application and save this image to disk. This can be accomplished either by system level checkpointing, or by using application level checkpointing libraries.
On Blue Gene, there is a scalability issue of checkpointing 65,536 compute node processors to persistent storage. Each compute node has 512 megabytes (up to 2 GB) of memory, or in total 32 gigabytes of memory per IO node. In all there are 1024 IO nodes, each potentially handling 32 gigabytes of checkpoint data, for a total of 32 terabytes stored to disk. Checkpointing causes an incredible load on the storage system and interconnect. Prior art techniques to overcome the checkpoint storage problems include incremental checkpointing or difference based checkpointing. Compression of the checkpoint storage but may be combined with these other checkpointing methods.
Incremental checkpointing or difference based checkpointing is a method to save only the differences between previous checkpoints. In this method, differences are calculated at each of the nodes from a template file or previous checkpoint. Each node saves its difference file through the file system to disk. Typically, the difference calculation requires both the template file and the data file to be available to the CPU, and thus the template file must be transferred to each compute node. Each node must then calculate differences from the template file, using significant aggregate CPU and bandwidth.
Without a way to checkpoint massively parallel computer systems that does not require the template file and the data file available to the CPU the super computers will need to continue to use a burdensome amount of network bandwidth and CPU time to checkpoint the progress of the software application.